There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Data Mining - Concepts and Techniques.

Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

A new bulk microphysical parameterization (BMP) has been developed for use with the Weather Research and Forecasting (WRF) Model or other mesoscale models. As compared with earlier single-moment BMPs, the new scheme incorporates a large number of improvements to both physical processes and computer coding, and it employs many techniques found in far more sophisticated spectral/bin schemes using lookup tables. Unlike any other BMP, the assumed snow size distribution depends on both ice water content and temperature and is represented as a sum of exponential and gamma distributions. Furthermore, snow assumes a nonspherical shape with a bulk density that varies inversely with diameter as found in observations and in contrast to nearly all other BMPs that assume spherical snow with constant density. The new scheme’s snow category was readily modified to match previous research in sensitivity experiments designed to test the sphericity and distribution shape characteristics. From analysis of four idea...

/pdf/explicit-forecasts-of-winter-precipitation-using-an-improved-200vx38jzm.pdf

Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization

This paper presents a new algorithm to identify and mitigate the second trip contamination for the polarmetric weather radar employing the random phase coding. The algorithm is based on an auto/cross-correlation function (ACF/CCF) multi-lag processing method and the optimal use of instantaneous phase from polarimetric channels. It is specially designed for polarimetric weather signals with a random phase. Therefore, it is convenient to be implemented in a magnetron weather radar. The data processing of C-band polarimetric weather radar OU-PRIME demonstrates the effectiveness of identification and mitigation of the second trip echo.

A new identification and mitigation algorithm for second trip contamination

The correlation effect of waves scattered from random media has attracted considerable interest in recent years. In particular, the angular correlation function (ACF) of waves scattered from rough surfaces and volumes has been studied extensively, and the characteristics of the angular memory effect (AME), which was first described by Feng et al. [1988], were reported for different surface conditions. Applications of AME, including height profiling in interferometric synthetic aperture radar (INSAR) and detection of buried objects, have been proposed and studied by researchers using numerical and experimental techniques. However, most of the recent studies of AME have been confined to the area of waves scattered from rough surfaces. In this paper we will investigate the angular memory signature of volume scatterers. Numerical and experimental studies on the ACF of waves scattered from randomly distributed cylinders are presented at millimeter-wave frequencies (80–105 GHz). It has been found that the angular width of ACF for volume scattering is narrower and shorter than that for random rough surfaces.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/98RS02199

The angular correlation function of waves scattered from randomly distributed cylinders

Configurable Phased Array Demonstrator (CPAD) was developed since 2010 for the scalable verification and risk mitigation of the Multi-Function Phased Array Radar (MPAR) at sub-array level. This work reviews the basic concepts and solutions of CPAD and focuses on the development of a single linear column array and multiple planned experiments of CPAD, to support the development of future Cylindrical Polarimetric Phased Array Radar (CPPAR). The paper describes several new developments related to CPAD: (1) Dual-polarized linear array as a "column" of a new CPPAR, (2) Scalable validation through laboratory measurements at different frequencies, (3) Virtual array through rotating platform, (4) Passive sensing with coordination of remote transmitters.

Supporting of cylindrical polarimetrie phased array radar development using configurable phased array demonstrators (CPAD)

Characterization of Hydrometeors

Recent studies indicate that at high frequencies, the branches and leaves in vegetation scatter independently. However, at low frequencies, they scatter collectively so that the structure of the trees and plants needs to be taken into account. Also, the near-field interaction among branches and leaves at low frequencies can give strong polarization signatures and cross polarization. Such collective scattering effects can contribute to a variety of frequency and polarimetric dependence. To take into account the tree and plant structures, the authors have used a stochastic Lindenmayer system to generate plant and tree structures with realistic appearances. They then solve Maxwell's equations for vegetation grown in this manner.

Guifu Zhang

Papers

A new identification and mitigation algorithm for second trip contamination

The angular correlation function of waves scattered from randomly distributed cylinders

Supporting of cylindrical polarimetrie phased array radar development using configurable phased array demonstrators (CPAD)

Characterization of Hydrometeors

Microwave scattering by plants generated by a stochastic Lindenmayer system